Automated Vocabulary Instruction in a Reading Tutor

Heiner, Cecily; Beck, Joseph E.; Mostow, Jack

doi:10.1007/11774303_86

Cited by 5 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…( 2 With these help methods, their efficiency should be measured so that they can be improved better in the future. Reading Tutor [6] has provided a good method-random test: 20 groups of users are randomly offered different methods of help, and the most popular method and the least effective method are summarized at the end of the experiment. In the future, the most popular method will be utilized widely, and the least effective method will be improved.…”

Section: Feedbackmentioning

confidence: 99%

Guitar recognizer - an artificial intelligence-based teaching software

2023

ACE

View full text Add to dashboard Cite

This article describes a preliminary idea for guitar teaching software, briefly describing its several components: sound recording, sound recognition, assessment methods, and a feedback system. The voice entry system is as uncomplicated as possible to avoid difficulties in user input. Users can use the most commonly used tool - microphone - to input. Two approaches to voice recognition are presented to suggest possible future implementations. This system is more difficult to implement because of the actual need to consider more external factors, such as noise, volume level, etc. The handling of these issues is the biggest challenge for this system. Three main aspects are considered in the assessment system, and more assessment elements are to be further explored. Some help methods are mentioned in the feedback system and how to test their help efficiency. At the same time, the feedback system turns some difficult techniques that may hinder the learning of beginners into bonus content, so as not to discourage them from learning. The conclusion presents some of the necessary databases for the software and other system issues that still need to be addressed. Some possible methods of implementation are discussed as well as a preliminary plan for future research that could be conducted.

show abstract

Section: Feedbackmentioning

confidence: 99%

Guitar recognizer - an artificial intelligence-based teaching software

2023

ACE

View full text Add to dashboard Cite

show abstract

“…The author uses a ten-fold crossvalidation, dividing the students randomly into ten disjoint sets, as illustrated in Figure 2. App trains on nine sets, tests on the held-out set, repeats this procedure for each set, and averages the results (Heiner, 2004). We evaluate the model by comparing the average results with those obtained from the models.…”

Section: Embedded Experiments and Evaluationmentioning

confidence: 99%

Assistant for math reviewing

Liu¹

2023

View full text Add to dashboard Cite

If students want to practice or review any knowledge, they may look for related exercises to improve their proficiency in the knowledge. But choosing exercises that fit students’ present proficiency by students themselves is difficult and wastes much time. The educational app: Assistant for math reviewing can find appropriate exercises automatically and dynamically for students to help them improve quickly and efficiently. This app gets students’ proficiency based on their performance in answering exercises and gives advice for students to review based on their proficiency. The author addresses the following questions: what kind of exercises or knowledge should students review? How often should students review? How Assistant for math reviewing helps students improve efficiently. This paper outlines how Assistant for math reviewing works, what benefits students can get from this app, why this app can offer benefits, and why this app is better than other tools for reviewing math.

show abstract

“…Many sources of knowledge have been utilized in order to help children learn vocabulary, including machine-readable dictionaries and thesauruses such as WordNet (Fellbaum 1998), pictures and sounds for concrete vocabulary, and explanations of words in terms of other words. While other work on tutoring reading (Aist 2001, 2002; Brown, Frishkoff and Eskenazi 2005; Heiner, Beck and Mostow 2006) has explored some of these other resources, VEGEMATIC focuses on providing additional contexts to help students learn the meaning of words, and thus VEGEMATIC is most related to prior work on generation and selection of example sentences.…”

Section: Relation To Prior Workmentioning

confidence: 99%

Generating example contexts to help children learn word meaning

Liu¹,

Mostow²,

Aist³

2012

Nat. Lang. Eng.

Self Cite

View full text Add to dashboard Cite

This article addresses the problem of generating good example contexts to help children learn vocabulary. We describe VEGEMATIC, a system that constructs such contexts by concatenating overlapping five-grams from Google's N-gram corpus. We propose and operationalize a set of constraints to identify good contexts. VEGEMATIC uses these constraints to filter, cluster, score, and select example contexts. An evaluation experiment compared the resulting contexts against human-authored example contexts (e.g., from children's dictionaries and children's stories). Based on rating by an expert blind to source, their average quality was comparable to story sentences, though not as good as dictionary examples. A second experiment measured the percentage of generated contexts rated by lay judges as acceptable, and how long it took to rate them. They accepted only 28% of the examples, but averaged only 27 seconds to find the first acceptable example for each target word. This result suggests that hand-vetting VEGEMATIC's output may supply example contexts faster than creating them manually. † This work, performed while the first author was a Master's student in the Language

show abstract

Automated Vocabulary Instruction in a Reading Tutor

Cited by 5 publications

References 2 publications

Guitar recognizer - an artificial intelligence-based teaching software

Guitar recognizer - an artificial intelligence-based teaching software

Assistant for math reviewing

Generating example contexts to help children learn word meaning

Contact Info

Product

Resources

About